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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/23263

Title: Forecasting Indoor Temperature Using Fuzzy Cognitive Maps with Structure Optimization Genetic Algorithm
Authors: Poczeta, Katarzyna
Yastrebov, Alexander
Papageorgiou, Elpiniki
Issue Date: 2016
Publisher: Springer International Publishing
Citation: Fidanova, S. (Ed.). Recent advances in computational optimization: Results of the Workshop on Computational Optimization WCO 2015, Springer International Publishing,p. 65-80
Series/Report: Studies in Computational Intelligence
Series/Report no.: 655
Abstract: Fuzzy cognitive map (FCM) is a soft computing methodology that allows to describe the analyzed problem as a set of nodes (concepts) and connections (links) between them. In this paper the Structure Optimization Genetic Algorithm (SOGA) for FCMs learning is presented for prediction of indoor temperature. The proposed approach allows to automatically construct and optimize the FCMmodel on the basis of historical multivariate time series. The SOGAdefines a newlearning error function with an additional penalty for coping with the high complexity present in anFCMwith a large number of concepts and connections between them. The aim of this study is the analysis of usefulness of the Structure Optimization Genetic Algorithm for fuzzy cognitive maps learning on the example of forecasting the indoor temperature of a house. A comparative analysis of the SOGA with other well-known FCM learning algorithms (Real-Coded Genetic Algorithm and Multi-Step Gradient Method) was performed with the use of ISEMK (Intelligent Expert System based on Cognitive Maps) software tool. The obtained results show that the use of SOGA allows to significantly reduce the structure of the FCM model by selecting the most important concepts, connections between them and keeping a high forecasting accuracy.
Notes: [Poczeta, Katarzyna; Yastrebov, Alexander] Kielce Univ Technol, Al Tysiaclecia Panstwa Polskiego 7, PL-25314 Kielce, Poland. [Papageorgiou, Elpiniki I.] Technol Educ Inst TEI Cent Greece, 3rd Km Old Natl Rd Lamia Athens, Lamia 35100, Greece. [Papageorgiou, Elpiniki I.] Hasselt Univ, Fac Business Econ, Campus Diepenbeek Agoralaan Gebouw D, B-3590 Diepenbeek, Belgium.
URI: http://hdl.handle.net/1942/23263
DOI: 10.1007/978-3-319-40132-4_5
ISI #: 000389695400005
ISBN: 9783319401317
ISSN: 1860-949X
Category: C1
Type: Proceedings Paper
Validation: ecoom, 2018
Appears in Collections: Research publications

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